Own the existing servicing cost attribution model end-to-end: master its inputs, logic, and business impact, then architect and deliver an AI-integrated replacement.
Design, develop, and maintain forecasting models using statistical techniques such as time series, regression, and machine learning to support operational contact forecasting, headcount planning, license forecasting, and budget planning.
Partner with internal stakeholders to frame planning and forecasting problems, develop supporting metrics and diagnostics, and enable high-quality decision-making.
Highlight opportunities for productivity and efficiency improvements through data insights from a budget and financial performance perspective.
Present analytical recommendations to leadership, drive timely decisions, and ensure clear and concise communication with cross-functional stakeholders.
Partner with operational planning and other analytical teams to understand the business context around headcount and workforce scheduling, and obtain the data needed to generate accurate forecasts.
Maintain a strong understanding of our evolving business and ever-changing technical environment.

Bachelor’s, Master’s, or PhD in a quantitative field (e.g., statistics, industrial engineering, operations research) and 5+ years solving forecasting, planning, or related quantitative problems.
Strong proficiency in SQL and Python or R, and hands-on experience with a modern cloud-native data platform (e.g., Databricks, Snowflake, BigQuery, or equivalent).
Experience building optimization models using linear programming techniques (e.g., CPLEX, Gurobi) is a plus.
Strong experience developing and validating statistical forecasting models, with disciplined approaches to performance measurement, backtesting, and robust error tracking.
Proven ability to independently structure ambiguous problems and select the appropriate analytical approach without predefined direction.
Clear, persuasive communicator with strong stakeholder management skills and the ability to influence senior leaders across technical and non-technical audiences.
Strong bias toward automation: treat repetitive manual work as avoidable drudgery and build durable, automated systems, delegating to machines what they can do more reliably and efficiently than humans.
High standards of humility, honesty, and ownership: you take responsibility for outcomes, invest in your own growth, and actively develop others.

Health care coverage
Affirm covers all premiums for all levels of coverage for you and your dependents
Flexible Spending Wallets
generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
Time off
competitive vacation and holiday schedules allowing you to take time off to rest and recharge
ESPP
An employee stock purchase plan enabling you to buy shares of Affirm at a discount

Analyst II, Quantitative Modeling – Forecasting

Key skills